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DatalisHQ

ZuckerBot

by DatalisHQ

zuckerbot_send_capi_event

Manually send a Facebook Conversions API event for debugging CAPI pipelines, testing stage mappings with real user data, or integrating custom workflows not covered by webhooks.

Instructions

Manually send a Conversions API event for a business contact/lead. Useful for debugging CAPI pipelines, testing stage mappings with real user data, or sending events from custom integrations not covered by the webhook. Authenticates with the business API key OR with an x-zuckerbot-webhook-secret header if using the webhook path.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fbcNoOptional pre-formatted Facebook click cookie (fb.1.<ms>.<fbclid>), forwarded raw — never hashed
fbpNoOptional Facebook browser ID cookie (_fbp), forwarded raw — never hashed. Improves match quality for every event
emailNoOptional contact email for identity matching
phoneNoOptional contact phone for identity matching
valueNoOptional event value override in major currency units
fbclidNoOptional Facebook click ID; the server builds a well-formed fbc cookie from it
lead_idNoOptional ZuckerBot lead ID for attribution matching
last_nameNoOptional last name for identity matching
crm_sourceNoOptional CRM source label override (e.g., 'hubspot', 'salesforce')
event_timeNoOptional ISO 8601 event timestamp. Defaults to now.
first_nameNoOptional first name for identity matching
business_idNoOptional business ID override (resolved from API key when omitted)
meta_lead_idNoOptional Meta Lead Gen Ads lead ID for attribution matching
source_stageYesCRM stage key to map to a Meta event (e.g., 'lead', 'salesqualifiedlead', 'customer')
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It discloses that it manually sends an event and authenticates via API key or header. However, it does not mention side effects, idempotency, error handling, or permissions. The behavior is partially transparent but lacks detail on what happens after sending.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three concise sentences with no wasted words. It front-loads the purpose, then adds use cases and authentication info. Each sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 14 parameters and no output schema or annotations, the description is adequate but not complete. It explains purpose and when to use but lacks details on return values, error scenarios, or rate limits. Some behavioral gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with well-described parameters (e.g., fbc, fbp, source_stage). The description itself does not add extra parameter semantics beyond the schema. Baseline of 3 is appropriate since schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool sends a Conversions API event manually for a business contact/lead. It provides specific use cases (debugging, testing mappings, custom integrations) and distinguishes from webhook-based sending. The verb 'send' and resource 'event' are precise.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly lists when to use the tool: debugging CAPI pipelines, testing stage mappings, sending events for custom integrations not covered by webhook. It also explains authentication methods. However, it does not explicitly state when not to use it, though the use cases imply boundaries.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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